NYC Taxi data

Import cuXfilter

[1]:

from cuXfilter import charts
import cuXfilter
from bokeh import palettes
from cuXfilter.layouts import double_feature
from cuXfilter.assets.custom_tiles import get_provider, Vendors


[3]:

cux_df1 = cuXfilter.DataFrame.from_arrow('../../../data/nyc_taxi_1.arrow')

Define charts

[5]:

chart1 = charts.cudatashader.scatter_geo(x='dropoff_x',
                                         y='dropoff_y',
                                         aggregate_fn='count',
                                         tile_provider=get_provider(Vendors.MAPBOX_DARK, access_token= MAPBOX_TOKEN), x_range=(-8239910.23,-8229529.24), y_range=(4968481.34,4983152.92))

chart2 = charts.bokeh.bar('passenger_count', data_points=9)

Create a dashboard object

[10]:

d1 = cux_df1.dashboard([chart1, chart2], layout=double_feature, theme=cuXfilter.themes.dark, title= 'NYC TAXI DATASET')

[11]:

#dashboard object
d1

[11]:

Starting the dashboard

  1. d1.show(‘url you want the dashboard to run’) remote dashboard

  2. d1.app(‘10.110.47.43:8888’) within the notebook: If you are using jupyter remotely, use this line instead of second, and replace url with current notebook url

[12]:

# preview
await d1.preview()
../_images/examples_NYC_taxi_example_11_0.png

Export the queried data into a dataframe

[9]:

queried_df = d1.export()

no querying done, returning original dataframe